According to popular consensus, millennials were born between 1981 and 1996, Gen Z between 1997 and 2012, and Gen Alpha from 2013 to the mid-2020s.
As customer expectations evolve, insight has become more important than ever. Traditional market-research methods are no longer enough, as businesses need real-time intelligence to understand changing attitudes. Artificial intelligence and generative AI (GenAI) are transforming how organisations collect, analyse and act on consumer data. These technologies can improve customer experience through personalised recommendations, stronger engagement and quicker responses to changing market conditions. AI models, behavioural analytics and neuroscience-based approaches are also offering deep insight into the subconscious factors that shape consumer decisions. As a result, neuromarketing is becoming a valuable tool for understanding consumer motivations and preferences.
However, the future of AI-powered insights will be shaped by concerns about sustainability. Although AI can help organisations improve efficiency, reduce waste and optimise operations, its considerable energy demands are under scrutiny. As environmental awareness becomes central to consumer decision-making, technology companies will face greater pressure to develop energy-efficient algorithms and computing systems.
An example of AI-driven product development involved George Young, a scientist at Rockwell Automation in the United States. He was engaged by a global leader in athletic footwear, apparel and accessories to address a challenge: Reducing the development cycle for simple products, which typically took between six and eight months. Consumer feedback indicated that customers wanted new shoe models to be introduced every few weeks.
Young established a database on the colours, shapes and fabric textures used in footwear and apparel production. He then created a product lifecycle management system that centralised historical design and product information. Using this data and a GenAI model trained on the latest consumer choices, he developed an algorithm that continuously generated a range of designs. The system considered previous purchases, current consumer trends and an individual’s browsing and purchasing history on the company’s online platform.
The project was implemented through the company’s online sales channel. Customers were shown a range of products, including T-shirts and leggings featuring varied patterns, designs and textures, which could be personalised while they browsed. Products and configurations frequently selected by users became more prominent in the recommendation system. Once a customer selected their preferred colour, style, and fabric for an item such as a shoe or shirt, the product could be ordered directly through the website. Crucially, the company kept the required product components available but assembled them into the final configuration only after the customer completed the purchase.
Mark McCrindle, founder of the Australian research firm McCrindle, coined the term “Gen Alpha”. The firm estimated that, by 2029, the spending power of Gen Alpha would reach $5.46 trillion. Other estimates suggest that the spending of Gen Alpha and Gen Z could grow three times faster than that of all other generations by 2030, together accounting for around one-third of the consumer market.
More than a typical generational transition, Gen Alpha is the first cohort to grow up entirely surrounded by technology, with apps, connectivity and smart devices integrated into their education and entertainment from early childhood. Consequently, they are expected to surpass earlier digital natives like Gen Z in their technological familiarity and competence.
The writer is an economic analyst and author
 "artificial intelligence, Technology, Millennials, Gen Z")